GIST-Embedding-v0 is an open-source text embedding model trained for strong performance on the MTEB benchmark. Built with the sentence-transformers framework, it converts sentences and paragraphs into dense vectors suitable for semantic search, clustering, and retrieval-augmented generation pipelines.
GIST Embedding is a Foundation models & chat product. It focuses on creating compact, high-performing embeddings for general-purpose semantic search and retrieval. It is built as an open-source project for machine learning engineers and RAG developers. GIST Embedding is open source under the Open Source license. It runs on the web and API.
Aivin Solatorio builds and maintains GIST Embedding, and the product first shipped in 2023. Key capabilities include text embedding, MTEB benchmark, and sentence similarity.
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